{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "import sys \n",
    "from os import getcwd, path\n",
    "sys.path.append(path.dirname(getcwd()))\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sb\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "%matplotlib inline\n",
    "\n",
    "sb.set_context('paper')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from utils.paper import survival_hyper_label_printer, fishers_exact_hyper_label_printer, mann_whitney_hyper_label_printer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'dataframe_hash': -9059328030452674214,\n",
      " 'provenance_file_summary': {u'cohorts': u'0.4.0+3.gda968fb',\n",
      "                             u'isovar': u'0.0.6',\n",
      "                             u'mhctools': u'0.3.0',\n",
      "                             u'numpy': u'1.11.1',\n",
      "                             u'pandas': u'0.18.1',\n",
      "                             u'pyensembl': u'1.0.3',\n",
      "                             u'scipy': u'0.18.1',\n",
      "                             u'topiary': u'0.1.0',\n",
      "                             u'varcode': u'0.5.10'}}\n",
      "inner join with pdl1: 29 to 29 rows\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Variants did not exist for patient 0979\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Variants did not exist for patient 7592\n",
      "Variants did not exist for patient 8214\n"
     ]
    }
   ],
   "source": [
    "from utils import data\n",
    "from cohorts.functions import missense_snv_count\n",
    "cohort = data.init_cohort(normalized_per_mb=False, exclude_patient_ids=set(), only_patients_with_bams=False)\n",
    "cohort_df = cohort.as_dataframe(on=missense_snv_count, join_with=['pdl1'])\n",
    "cohort_df['Benefit'] = cohort_df['is_benefit']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0    9\n",
       "2.0    7\n",
       "3.0    6\n",
       "4.0    3\n",
       "0.0    1\n",
       "Name: 5-factor score, dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cohort_df['5-factor score'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def LiverMets(row):\n",
    "    if np.isnan(row['Liver Mets']):\n",
    "        return np.nan\n",
    "    return row['Liver Mets'] > 0\n",
    "\n",
    "def VisceralMets(row):\n",
    "    if np.isnan(row['Visceral Mets']):\n",
    "        return np.nan\n",
    "    return row['Visceral Mets'] > 0\n",
    "\n",
    "def FiveFactorScore01(row):\n",
    "    if np.isnan(row['5-factor score']):\n",
    "        return np.nan\n",
    "    return row['5-factor score'] == 0 or row['5-factor score'] == 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Has Liver Mets  False  True \n",
      "Response                    \n",
      "DCB                 7      2\n",
      "No DCB             11      9\n",
      "Fisher's Exact Test: OR: 2.86363636364, p-value=0.411832545266 (two-sided)\n",
      "{{{livermets_plot}}}\n",
      "{{{livermets_benefit:22%}}}\n",
      "{{{livermets_no_benefit:45%}}}\n",
      "{{{livermets_fishers:n=29, Fisher's Exact p=0.41}}}\n"
     ]
    },
    {
     "data": {
      "image/png": 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333wTwKM7qJ6Ur68vzp07h8zMTFVbZmYmzpw5Az8/vxrX7dOnDxo3boxffvlFrf3nn3+G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\nZGGAEBGRLAwQIiKShQFCRESy/H8yliIN+n8GywAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc68a210810>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mets = cohort.plot_benefit({'Has Liver Mets': LiverMets}, plot_col = 'Has Liver Mets')\n",
    "fishers_exact_hyper_label_printer(mets, 'livermets')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Has Visceral Mets  False  True \n",
      "Response                       \n",
      "DCB                    6      3\n",
      "No DCB                 4     16\n",
      "Fisher's Exact Test: OR: 8.0, p-value=0.0316777675099 (two-sided)\n",
      "{{{viseralmets_plot}}}\n",
      "{{{viseralmets_benefit:33%}}}\n",
      "{{{viseralmets_no_benefit:80%}}}\n",
      "{{{viseralmets_fishers:n=29, Fisher's Exact p=0.032}}}\n"
     ]
    },
    {
     "data": {
      "image/png": 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06mT1gaxfvx75+fmwtLTEgwcPpHZPT0+EhITgwoULWivwRQUFBZgxYwYyMjKwatUqNG7c\nGNeuXUNISAhq1aqFzz//XGvnLioqwt27d7V2/OokPz9f+m9SUpKOq9G9Jk2aoFatCt8NJqr2ZAVI\ndHQ0BEHA1q1bMWTIEKm9WbNmAFChFQkVCkWJ64dkZ2eXOynjjz/+iOjoaBw9elTqQ3Fzc0O9evWw\nYMECjBo1Ci1atJBdS0XcvXsX2z/8EPVNTLRy/OrkQWHh8//+8w/CJ07UcTW6lfHkCcb+v/8He3t7\nXZdCVOVkBUjxrSUnJyeV9uK/RB89eiT7hE5OToiLi1Nrj4uLg6OjY5n73rp1C2ZmZmpzcv3nP/+B\nKIqIj4/XWoAAQH0TE1jVrau141cXtR8/BgoLUdvAgD8PohpM1nW3paUlAOCff/5Raf/ll18AAA0a\nNJB9Qg8PD1y5cgXJyclSW3JyMi5duoSePXuWua+VlRVycnLUbiVduXIFgiCgUaNGsusgIqJXIytA\nOnToAADw9/eX2saPH4/ly5dDEAR07NhR9gm9vLxga2sLPz8/REREICIiAlOnToWNjQ1GjBghbadU\nKvH2229jw4YNUtvQoUPxxhtvYOLEidi3bx/++OMPfPvtt1ixYgVatWqFdu3aya6DiIhejawAmTx5\nMoyNjaFUKiEIAgDg7NmzKCoqgrGxMSZMmCD7hCYmJggLC4ODgwMCAwMREBCApk2b4vvvv4fJC/0L\nJU2TYmtri927d+Ott97C119/jY8//hg//fQTRo4cia1bt8qugYiIXp2sPhBHR0d8++23mD9/PhIT\nE6V2BwcHLF68uNy+i5c1btwYwcHBZW5ja2uLGzdulFjLmjVrKnQ+IiKqfLICBHj+tNOhQ4eQlJSE\njIwM1K9fn0+eEBHVYLIDpJi9vT2Dg4iI5PWBzJo1C2+99RbWr1+v0r5+/Xq89dZbJa4RQkRErzdZ\nAXLp0iUAwKBBg1TaBw8eDFEUcfHixcqvjIiI9JqsALl37x6A5+MwXlQ8/iMjI6OSyyIiIn0nK0CK\n19govhIpVvw9Z8ElIqp5ZAWIs7MzRFFEUFAQ9u/fj+vXr2P//v2YN28eBEGAs7OztuskIiI9I3tJ\n27/++gvp6emYO3eu1C6KIgRBqNQlb4mIqHqQdQUyfPhw9O7dW2V0ePEI8T59+mDYsGFaLZKIiPSP\n7HEgwcHBCA8PR2RkpDSQ0MPDA/369dNmfUREpKcqNJCwf//+6N+/v7ZqISKiakTWLazbt28jKioK\nsbGxAIDY2FhMmDABAwYMwLJly1D4vwsMERFRzSHrCmTdunUIDw9HYGAgWrRoAT8/P6SmpkIURSQk\nJEChUGDKlCnarpWIiPSIrCuQv//+GwDw7rvvIiYmBkqlEiYmJrC2toYoiggPD9dqkUREpH8qNBLd\n1tYWt27dAgD4+flh+/btAKC2QiAREb3+ZAVIcR+HKIqIi4uDIAhwcXGRlpAtKirSXoVERKSXZPWB\nNGjQACkpKQgKCpKmL2nWrJk0B5aFhYX2KiQiIr0k6wqka9euEEURx44dw7179/Dmm2/CxsZGWjGw\nWbNmWi2SiIj0j6wAmT59Orp16wYTExM4Oztj2bJlAIDLly+jadOm6NGjh1aLJCIi/SPrFpaFhQVC\nQ0PV2mfOnImZM2dWelFERKT/ZF2BEBERvazUKxBvb28IgoCwsDB4e3uXeZDi7YiIqOYoNUAuXLiA\nWrVqSf8WBKHE7YqndCciopqlzD6Q4inbX/43ERFRqQFSPHHiy/8mIiICyuhE37t3Lx4/flyVtRAR\nUTVSaoAEBQXh3XffxaeffoqoqChOV0JERCrK7APJy8vDoUOHcOjQIVhYWKB///4YNGgQ3nnnnaqq\nj4iI9FSpVyDvv/8+TExMpPXPHzx4gB9++AEjRoxA3759sWHDBs7CS0R6JSYmBosXL0ZMTIyuS6kR\nSg2QVatW4dy5c1izZg08PT1hZGQkhUlSUhLWrVuH3r17Y9SoUdi1a1dV1kxEVKLt27fj5MmT0lIT\npF1l3sIyNjZGv3790K9fPzx8+BBHjhzBwYMH8ccff0hTvF+6dAmXL1/GyJEjq6RgIqLSFD/4wweA\nqobsqUzq1auHDz74AFu3bsWxY8fQoUMHbdZFRER6TtZkisDzgYRnz57Fb7/9huPHj+Phw4cQBIED\nDImIaqhyA+TSpUs4ePAgDh8+LC0g9WJo2NjYYODAgdqrkIiI9FKpAbJ69WocPHgQSqVSaisODlNT\nU/Tt2xeDBg2Cu7u79qskIiK9U2qAhIaGqtyiMjQ0RPfu3TFo0CD06NEDRkZGVVYkERHpn3InU2zT\npg0GDRqEfv36wdzcvKrqIiIiPVdqgEybNg2DBg1CkyZNqrIeIiKqJkoNkKlTp1ZlHUREVM3oZEnb\ntLQ0TJ8+HW5ubmjXrh2mTZuG1NRU2fvHx8djxowZ6NixI1xdXdG3b1+OPCUiqmKyx4FUlry8PHh7\ne8PY2BgrVqwAAKxZswY+Pj44cOAA6tSpU+b+165dg6+vLzp06IAlS5bA1NQUSUlJePToUVWUT0RE\n/6vKA2T37t1ISUnB4cOHpf4VZ2dn9OnTB7t27YKvr2+p+4qiiLlz5+Ldd99FcHCw1N6+fXttl01E\nRC+p8ltYkZGRcHV1Vemct7OzQ9u2bREREVHmvufPn0dCQkKZIUNERFWjygMkLi4OzZs3V2t3cnJC\nfHx8mfv+9ddfAJ7fBhsxYgRatWqFzp0744svvkB+fr5W6iUiopLJCpDbt28jKipKWhs9NjYWEyZM\nwIABA7Bs2TJpZl45srKyoFAo1NoVCgVycnLK3Pfff/+FKIqYOXMmunbtiu+++w4TJ07ETz/9hNmz\nZ8uugYiIXp2sPpB169YhPDwcgYGBaNGiBfz8/JCamgpRFJGQkACFQoEpU6Zou1aIoghBEDB48GD4\n+/sDANzd3fHs2TOsXr0aCQkJaNasmdbrICIimVcgf//9NwDg3XffRUxMDJRKJUxMTGBtbQ1RFBEe\nHi77hAqFAtnZ2Wrt2dnZMDMzK3Pf4pHwnTt3Vmnv0qULRFGUrpBIu4xe+i8R1UyyAuTevXsAAFtb\nW9y6dQsA4OfnJ429qMjStk5OToiLi1Nrj4uLg6OjY7n7ku61MzaGk6Eh2hkb67oUItIhWQFS3Mch\niiLi4uIgCAJcXFzQqFEjAEBRUZHsE3p4eODKlStITk6W2pKTk3Hp0iX07NmzzH27deuG2rVr4/Tp\n0yrtv//+OwRBwH/+8x/ZdZDmGhsYoJeJCRobGOi6FCLSIVkB0qBBAwBAUFAQDhw4AABo1qyZtD6I\nhYWF7BN6eXnB1tYWfn5+iIiIQEREBKZOnQobGxuMGDFC2k6pVOLtt9/Ghg0bpDZzc3NMmjQJu3bt\nwpo1a3Du3DmEhoZiw4YNGDp0KOftIiKqQrI60bt27YqdO3fi2LFjEEURzZo1g42NDSIjIwGgQh3X\nJiYmCAsLw5dffonAwECIoojOnTsjKCgIJiYm0naiKEpfL/L390e9evWwc+dObN26FVZWVpg4cWKV\ndOITEdH/kRUg06dPR0pKCqKjo2FnZ4cvvvgCAHD58mU0bdoUPXr0qNBJGzdurDKSvCS2tra4ceNG\nia/5+vpyMCERkY7JChALCwuEhoaqtc+cORMzZ86s9KKIiEj/6WQ2XiIiqv5kT6Z44cIFbNu2DYmJ\nicjLy1N5TRAEHD9+vNKLIyIi/SUrQM6ePYuJEyeiqKhI6tQWBAHA/40OJyKimkVWgGzZskVlvitB\nENSejiIioppF9lQmgiBg48aNUtvFixfh5eUFBwcH6XFeIiKqOWQFyMOHDwEAHTt2lNpMTEwwZ84c\n3L59G4sWLdJOdUREpLdkBUjdunUBAAYGBtJgv+vXr0tzZJ0/f15L5RERkb6S1QdSv3595ObmIjMz\nE/b29rh58ybGjh2LWrWe509xwBARUc0h6wrExcUFoiji77//Rt++fSGKIgoKCvDkyRMAQK9evbRa\nJBER6R9ZVyABAQHw9fWFjY0NunTpAqVSiUOHDsHAwAC9evVCQECAtuskIiI9IytArK2tYW1tLX2/\naNEidpwTEdVwnMqEiIg0UuoVSHmLO72IU5kQEdU8pQZISkqK2hQlL09jUtzGqUyIiGqeMvtAXp6u\n5MX5r4iIqGYrNUAiIiJUvhdFEZ6enhAEQe01IiKqeUoNEFtb21J3Kus1IiKqGfgUFhERaYQBQkRE\nGin1Fta+fftK3amk14YMGVI5FRERUbVQaoDMnTtX7fHc4u+DgoLU2hkgREQ1S4Ue4yUiIipWaoAM\nHTq0KusgIqJqptQAWbp0aVXWQURE1QyfwiIiIo0wQIiISCMMECIi0ggDhIiINMIAISIijTBAiIhI\nI7ICxMPDA56eniW+FhQUhHnz5lVqUUREpP9kBYhSqURKSkqJr+3duxd79+6t1KKIiEj/vdItrPT0\n9Mqqg4iIqplSR6KHhYVh27ZtKm09e/ZU+T4zMxMAYGlpqYXSiIhIn5UaILm5uUhJSVFZB72021gd\nO3bUTnVERKS3Sg0QU1NT2NjYAHjeByIIAqytraXXBUGAubk5WrduDX9/f+1XSkREeqXUAPHx8YGP\njw8AwMXFBQBw4sSJqqmKiIj0nqxO9G3btiEsLKzSTpqWlobp06fDzc0N7dq1w7Rp05Camlrh44SG\nhsLFxQVjxoyptNqIiEieMheUKta+fXsAwP3796FUKpGfn6+2jbu7u6wT5uXlwdvbG8bGxlixYgUA\nYM2aNfDx8cGBAwdQp04dWce5e/cuvvnmGzRo0EDW9kREVLlkBcj9+/cREBCAc+fOlfi6IAiIiYmR\ndcLdu3cjJSUFhw8fRpMmTQAAzs7O6NOnD3bt2gVfX19Zx/n8888xaNAgJCQkoKioSNY+RERUeWTd\nwlq0aBHOnj0LURRL/ZIrMjISrq6uUngAgJ2dHdq2bYuIiAhZx/j1119x48YNzJo1S/Z5iYiocsm6\nAvnjjz8gCAIsLS3Rrl071K1bV3q8t6Li4uLUxpMAgJOTE44cOVLu/jk5OVi2bBkCAgJgZmamUQ1E\nRPTqZAVI8RXGzp070bRp01c6YVZWFhQKhVq7QqFATk5OufsvX74cb775JoYMGfJKdRAR0auRdQur\nW7duAAADAwOtFlOe6OhoHDhwAAsXLtRpHUREJDNAxowZA1NTU0ybNg1RUVG4c+cOlEqlypdcCoUC\n2dnZau3Z2dnl3pL67LPPMGzYMDRs2BC5ubnIyclBYWEhCgsLkZubi4KCAtl1EBHRq5F1C2vUqFEQ\nBAE3btzA5MmT1V6vyFNYTk5OiIuLU2uPi4uDo6NjmfvGx8cjISEBO3fuVHutffv2CAoKgre3t6w6\niIjo1cgKEAAVetKqLB4eHli5ciWSk5NhZ2cHAEhOTsalS5cwe/bsMvfdvn27WtuSJUtQVFSEBQsW\nqDzZRURE2iUrQIYOHVppJ/Ty8sKOHTvg5+eHGTNmAACCg4NhY2ODESNGSNsplUp4enrC398ffn5+\nAEoerGhqaoqioiK4ublVWo1ERFQ+WQGydOnSSjuhiYkJwsLC8OWXXyIwMBCiKKJz584ICgqCiYmJ\ntF1Fxpho+kgxERFpTvYtrGIZGRnIysoqt7+iLI0bN0ZwcHCZ29ja2uLGjRvlHquk21pERKR9slck\nvHjxIgYPHowuXbpg4MCBAICZM2fC29sbly9f1lqBRESkn2QFyM2bNzFu3DjcunVL5baSo6MjLly4\ngPDwcK0WSURE+kdWgKxfvx75+fmwsLBQaff09AQAXLhwofIrIyIivSYrQKKjoyEIArZu3arS3qxZ\nMwDP1/cgIqKaRVaAFM9R5eTkpNJevC7Io0ePKrksIiLSd7ICxNLSEgDwzz//qLT/8ssvAMBFnYiI\naiBZAdKhQwcAgL+/v9Q2fvx4LF++HIIgoGPHjtqpjoiI9JasAJk8eTKMjY2hVCqlQXtnz55FUVER\njI2NMWHCBK0WSURE+kdWgDg6OuLbb7+Fg4ODyghxBwcHbN68+ZUGFRIRUfUkeyS6m5sbDh06hKSk\nJGRkZKB+/fqwt7fXZm1ERKTHKjyVib29PYODSI8UFRXh7t27ui5DLxQ/GZqfn4+kpCQdV6N7TZo0\nQa1asieTJPOYAAAXl0lEQVQcqTBZATJr1iyEh4fD398fU6dOldrXr1+PkJAQ9O/fH1999ZXWiiSi\n0t29exf+X27BG2aWui5F5zKVGQCARGUGAkP26rga3XqU8wAh88Zr9Q9+WQFy6dIlAMCgQYNU2gcP\nHox169bh4sWLlV8ZEcn2hpklTC34OH2uYW08A2BoWJs/jyog69rm3r17AAArKyuV9uLxHxkZGZVc\nFhER6TtZAWJsbAzg/65EihV/X6dOnUoui4iI9J2sAHF2doYoiggKCsL+/ftx/fp17N+/H/PmzYMg\nCHB2dtZ2nUREpGdkL2n7119/IT09HXPnzpXaRVGEIAiVuuQtERFVD7KuQIYPH47evXurDCIsXhOk\nT58+GDZsmFaLJCIi/SN7HEhwcDAOHTqEEydOSAMJPTw80K9fP23WR0REeqrcACkoKEBoaKh0q4qB\nQUREgIwAMTIywsaNG1FYWAgfH5+qqImIiKoB2ZMpAkBeXp5WiyEioupDVoBMmzYNgiDgq6++kuaa\nISKimk1WJ3pYWBhMTU2xb98+RERE4M0335QGFwKAIAgICwvTWpFERKR/ZAXIn3/+KS0klZubi6tX\nr0qvFY8FISKimkX2Y7zF4z6IiIgAmQESGxur7TqIiKia0d5KI0RE9FqTfQuroKAAO3bswJkzZ5Cd\nnY09e/bg119/RWFhIbp16wZLSy5mQ0RUk8gKkLy8PIwdOxbXr19X6TQ/efIkwsPDERAQgI8++kir\nhRIRkX6RdQvrm2++wbVr19Q60gcPHgxRFBEVFaWV4oiISH/JCpDDhw9DEAQEBASotLu6ugIAF68n\nIqqBZAWIUqkEAIwZM0al3cTEBABw//79Si6LiIj0XYWWtH306JFK+/Xr1wH8X5AQEVHNIStAWrRo\nAQBYtWqV1Pbbb78hICAAgiDAxcVFO9UREZHekhUgI0eOhCiK2Lt3r/QE1pw5c5CcnAwA8PLy0l6F\nRESkl2QFyMCBAzFmzJgSl7QdNWoU3n//fa0WSURE+kf2QML58+dj4MCBiIyMxIMHD2BpaYkePXqg\ndevW2qyPiIj0lKwAycrKAgC0bt2agUFERADKCZDjx49j+fLlUl9H06ZNMWfOHHh6er7SSdPS0vDl\nl1/i7NmzEEURnTt3xrx582BtbV3mfteuXcOuXbsQHR2N9PR0WFhYoF27dvjkk09gZ2f3SjUREVHF\nlNoHEh0djenTpyM5OVnq80hKSsL06dPx559/anzCvLw8eHt7IzExEStWrMDKlStx+/Zt+Pj4lLtk\nbnh4OOLj4+Ht7Y3Nmzdj9uzZiImJwQcffID09HSNayIiooor9Qrk22+/RVFRkVp7UVERtmzZAnd3\nd41OuHv3bqSkpODw4cNo0qQJAMDZ2Rl9+vTBrl274OvrW+q+EydOVJu0sU2bNujZsyf27NmDadOm\naVQTERFVXKlXIFeuXIEgCBg5ciT++OMPnDt3DiNGjAAAXL58WeMTRkZGwtXVVQoPALCzs0Pbtm0R\nERFR5r4lzfhrY2MDS0tLXoEQEVWxUgMkOzsbwPPxHgqFAhYWFpgzZw4AICcnR+MTxsXFoXnz5mrt\nTk5OiI+Pr/Dx4uPjkZGRAScnJ41rIiKiiis1QIpvX73xxhtSW7169QC82vK2WVlZUCgUau0KhaLC\nwVRYWIjPPvsM9evXxwcffKBxTUREVHHlPsYbEhIiq93f379yKqqAhQsX4vLly9i8eTNMTU2r/PxE\nRDVZuQGyfv16le+LpzJ5uV1ugCgUCun22Iuys7NhZmYm6xjA83m5fvrpJyxfvhydOnWSvR8REVWO\nMgNE7q2q4lCRw8nJCXFxcWrtcXFxcHR0lHWMb775Blu2bJFGxxMRUdUrNUC0dUvKw8MDK1euRHJy\nsjT4Lzk5GZcuXcLs2bPL3X/btm34+uuv8emnn2L06NFaqZGIiMpX5QHi5eWFHTt2wM/PDzNmzAAA\nBAcHw8bGRnpMGHi+iJWnpyf8/f3h5+cHADh48CCWLl2Kbt26oUOHDrhy5Yq0fb169WRfwRAR0auT\nPZliZTExMUFYWBi+/PJLBAYGSlOZBAUFqSxM9fKsvwBw+vRpAMCpU6dw6tQpleO6u7tj27ZtVfMm\niIio6gMEABo3bozg4OAyt7G1tcWNGzdU2pYuXYqlS5dqszQiIpJJ1nogREREL2OAEBGRRhggRESk\nEQYIERFphAFCREQaYYAQEZFGGCBERKQRBggREWmEAUJERBphgBARkUYYIEREpBEGCBERaYQBQkRE\nGmGAEBGRRhggRESkEQYIERFphAFCREQaYYAQEZFGGCBERKQRBggREWmEAUJERBphgBARkUYYIERE\npBEGCBERaYQBQkREGmGAEBGRRhggRESkEQYIERFphAFCREQaYYAQEZFGGCBERKQRBggREWmEAUJE\nRBphgBARkUYYIEREpBEGCBERaYQBQkREGmGAEBGRRnQSIGlpaZg+fTrc3NzQrl07TJs2DampqbL2\nLSgowPLly9GlSxe4urpi5MiRiI6O1nLFRET0sioPkLy8PHh7eyMxMRErVqzAypUrcfv2bfj4+CAv\nL6/c/YOCgvDzzz/jk08+waZNm2BlZYXx48cjNja2CqonIqJihlV9wt27dyMlJQWHDx9GkyZNAADO\nzs7o06cPdu3aBV9f31L3jY2NxcGDB7Fs2TIMGTIEAODu7o4BAwYgODgYGzZsqIq3QERE0MEVSGRk\nJFxdXaXwAAA7Ozu0bdsWERERZe4bERGB2rVro1+/flKbgYEBBgwYgNOnT+Pp06daq5uIiFRVeYDE\nxcWhefPmau1OTk6Ij48vc9/4+HjY2dnB2NhYbd+nT5/izp07lVorERGVrsoDJCsrCwqFQq1doVAg\nJyenzH2zs7NL3Nfc3Fw6NhERVY0q7wPRhcLCQgDPn/7SVFpaGpIePkT2s2eVVRa9BrLy8pCWlgYD\nAwOd1ZCWloas9LvIf1z2H2A1wZMnj1D47BmePHmE+ykJui5Hp57kZr/yZ7P4d2bx79CXVXmAKBQK\nZGdnq7VnZ2fDzMyszH3NzMygVCrV2ouvPIqvRF527949AMCYMWMqWi5RufZ6e+u6BFKThpQEPpnp\n/cdvlXKce/fuwd7eXq29ygPEyckJcXFxau1xcXFwdHQsd9/jx48jPz9fpR8kLi4OtWvXRtOmTUvc\nr1WrVvjhhx9gZWWl078UiYiqk8LCQty7dw+tWrUq8fUqDxAPDw+sXLkSycnJsLOzAwAkJyfj0qVL\nmD17drn7rlu3DocOHZIe4y0sLMShQ4fQpUsX1K5du8T96tSpAzc3t8p9I0RENUBJVx7FDD7//PPP\nq64UoEWLFggPD8eRI0fQsGFDJCYm4rPPPoOJiQm++OILKQSUSiU6dOgAQRDg7u4OALCyskJCQgJ2\n7NgBc3Nz5OTkYNWqVbh27RpWrVqFBg0aVOVbISKq0ar8CsTExARhYWH48ssvERgYCFEU0blzZwQF\nBcHExETaThRF6etFy5Ytw5o1a/D1118jNzcXLi4u2LJlC1xcXKr6rRAR1WiC+PJvaCIiIhk4Gy8R\nEWmkRowDeZ3t3bsXQUFBMDMzQ0REBExNTaXXCgsL0bJlS/j7+8Pf37/SzlXMxMQEFhYWePvttzFg\nwACVKWZelJmZia1btyIyMhIpKSkQRRFNmjRBjx494O3tLfVdeXh4qDymbWJigiZNmsDLywsffvjh\nK9dP1YcmnzV+zqoeA+Q1kZubi82bN+PTTz/V6nkEQUBwcDAaNWqEgoICKJVKREVFYdasWdizZw82\nbdoEIyMjafu4uDiMGzcOgiDA29sbLVu2BADcuHEDu3fvRmJiItatWydt37VrV0ybNg0A8PDhQ0RG\nRuKLL77As2fPypxok14/Ffms8XOmIyJVa7/88ovYokULcfz48WLr1q3FjIwM6bVnz56JLVq0ENet\nW1dp53JxcRHv3Lmj9trRo0dFFxcXcfHixSrn79u3r9i7d2/xwYMHavsUFhaKJ0+elL7v0aOHOGfO\nHLXtRo0aJXp5eVXKe6DqoSKfNX7OdId9IK8BQRAwZcoUAJA1pf3Vq1fh6+uLNm3aoE2bNvD19cXV\nq1dfqYZevXqhZ8+e+PHHH5Gfnw8AOHr0KBITEzF79mxYWFio7VOrVi1079693GPXq1ePMy2T5OXP\nGj9nusMAeU00bNgQY8aMwZ49e8pc3TE2NhZjx45Fbm4uVqxYgRUrVuDhw4cYO3Ysbt68+Uo1dO/e\nHQUFBbh27RoA4Ny5czA0NES3bt1kH0MURRQWFqKwsBA5OTnYt28fzp49iwEDBrxSbfR6efGzxs+Z\n7rAP5DUyceJE7N69GyEhIViyZEmJ22zYsAHGxsYICwtDvXr1AACdOnVCz549sX79egQHB2t8fmtr\na4iiKM09lpqaCgsLC7Xp98vy66+/4tdff5W+FwQBw4cPx/jx4zWui14/1tbWAJ7P0cTPme4wQF4j\nCoUCH330ETZs2ICJEyeqLNpVLDo6Gu+9954UHsDzS3cPDw9ERka+0vnF/x1SJAiCxsfo3r07ZsyY\nAVEU8eTJE1y7dg0hISEwNDTEggULXqk+en286meNn7PKwVtYrxlfX1+YmZmVeiWRnZ0NKysrtfYG\nDRqUux5LedLS0iAIgnR8a2trZGZmSn0icigUCrz99tto2bIl3Nzc8NFHH8HPzw87d+4sd8ExqjmK\npxm3srLi50yHGCCvmbp162LSpEk4fPgwbty4ofa6QqHA/fv31drv379f7nT65YmMjISxsbE0c2en\nTp1QWFiI33///ZWO6+TkBAC4devWKx2HXh8vftY6deqEZ8+e8XOmAwyQ19Do0aPRqFEjrF27Vu0S\n393dHVFRUXj8+LHU9vDhQ5w4cQIdOnTQ+JxHjhxBZGQkRo0aJd2L7t27NxwcHLBq1So8ePBAbZ/C\nwkJERUWVe+zizn1LS0uN66PXx8uftd69e+PNN9/k50wH2AfyGjIyMoKfnx/mz5+vFiB+fn6IioqC\nj48PJk6cCADYvHkz8vPzMXXq1HKPLYoiYmJi8ODBAzx9+hRKpRInT57E4cOH0aVLF8ycOVPa1sDA\nACEhIRg3bhyGDBkCb29v6eokNjYWe/bsgaOjo8ojlpmZmbhy5QoAIC8vD1euXMHGjRvx1ltvSbMy\nU80g97PGz5nucDLFam7v3r2YN28ejh49qtJpXlhYiP79++POnTuYOnWqylQmV69exdq1a3H58mWI\noog2bdrg008/LXXRmJfPVczY2BiWlpZo2bIlBg4ciN69e5e4X1ZWFrZu3YoTJ05IU0zY29vDw8MD\nY8eOlf7i8/DwUHkE2cjICDY2NvD09MTEiRNf+RYbVR+afNb4Oat6DBAiItII+0CIiEgjDBAiItII\nA4SIiDTCACEiIo0wQIiISCMMECIi0ggDhIiINMKR6PRaCwkJQUhIiEqboaEhGjZsiE6dOmHatGlo\n3Lixjqojqt54BUI1giAI0ldhYSFSU1Px888/Y/To0Xjy5ImuyyOqlhggVGNMnToVN27cwMGDB6UF\niVJTUxEREaHjyoiqJ97CohqnWbNm6N27N77//nsAgFKplF5LT0/Hhg0bcPr0aaSnp6Nu3bpwdXXF\nxx9/DDc3N2m7zMxMBAcH49SpU7h//z4MDAxgZWWFli1bYtq0aXBwcAAAuLi4AHg+C/KECROwdu1a\nxMfHo0GDBhg9ejQmTJigUtvNmzexadMmXLhwAVlZWahXrx5at26NCRMmqJz/xVtz69evx+nTp3H0\n6FHk5+fD1dUVCxYsgL29vbT90aNHERYWhoSEBDx8+BAKhQIODg7o2bMnPvroI2m7+Ph4bNy4EX/8\n8QcePHgAMzMzuLm5YerUqWjRokXl/A9Arw0GCNVIL04BV79+fQBAQkICRo8ejaysLGkW49zcXJw6\ndQpnzpzBV199hX79+gEAAgMD8fvvv6vMdpyUlISkpCQMGjRIChDg+e2zW7duYcqUKdJ5lUolVq1a\nhSdPnmDatGkAgPPnz2PSpEkoKCiQjpudnY2TJ0/i999/x4oVK/D++++rvA9BEBAUFITc3Fyp7cyZ\nM5gyZQoOHjwIQRBw9epVfPLJJyrvOSMjAxkZGcjLy5MCJDo6GhMmTFBZmCkzMxNHjx5FVFQUtm7d\ninbt2mn4E6fXEW9hUY0THx+PY8eOAXi+AFePHj0AAEuWLEFWVhbMzMywbds2XL16FUeOHEGzZs0g\niiIWL16MZ8+eAXj+y1YQBPTq1QvR0dG4ePEiDhw4gMDAQDRq1EjtnDk5OZg5cyaio6OxZcsW1KlT\nB8DzqfQzMzMBAJ999hmePn0KQRCwcOFCXLx4UVpmtfj8eXl5asc2NTXF/v37cerUKTRr1gwAkJiY\niKtXrwIALl68iKKiIgDA7t27cf36dURFRWHjxo0qgTR//nzk5+fDxsYGv/zyC65du4a9e/fC0tIS\nBQUFWLRoUaX8/On1wSsQqjFefiLL3t4eS5YsgaWlJfLz83H+/HkIgoCcnByMHTtWbf/MzEzExMTg\nnXfegZ2dHW7duoVLly5hw4YNcHJygrOzM3x8fEpcp7tRo0bS+iudO3eGp6cnfvvtNzx9+hTR0dFo\n3rw5kpKSIAgCWrRoAS8vLwBAz5498d577+H48ePIycnBpUuX0KlTJ5Vjjxs3Ds7OzgCAbt26SUuy\npqSkwNXVFXZ2dtK2mzZtQrt27dCsWTO888470hoZSUlJSExMhCAISElJwdChQ9Xew61bt5CRkSFd\nsRExQKjGePEXuyiKyMvLw9OnTwE8X0uisLBQelKrtP2Lrxa++OILzJ07F4mJidi6dat0e8jGxgYb\nNmyQ+j6KvfyosI2NjfTvzMxMlZX0ijv4S9q2pBX3iq86gOdXVMUKCgoAAL169cKYMWPw008/4cSJ\nEzhx4gREUYSBgQFGjhyJ+fPnIyMjo8Sf08vvPysriwFCEgYI1RhTp07F5MmTceTIEQQEBCA9PR3+\n/v44ePAgLCwsYGBggKKiItjb2+Pw4cNlHuudd95BeHg4lEolEhISEBsbiw0bNiA1NRWrVq3Ct99+\nq7J9enq6yvcvdtxbWFio/FJ+cbGjl78vablVQ8P/+79xab/858+fj8DAQNy8eRNJSUn49ddfERUV\nhR07dmDQoEEq5+/cuTO2bNlS1tsnAsA+EKphDA0NMWDAAIwePRoA8PjxY6xatQrGxsbo2LEjRFFE\nUlISVq5cKS2lmpCQgO+++w4+Pj7ScdasWYPIyEjUqlULHTp0QN++faFQKCCKoloAAEBaWho2b96M\nR48e4cyZMzh+/DgAoHbt2nBzc4O9vT0cHBwgiiJu3ryJPXv24PHjxzhx4gQiIyMBAGZmZmjTpk2F\n3/Off/6JzZs3IyEhAQ4ODujduzdcXV2l15VKpcr5z507h7CwMOTm5qKgoACxsbEICQlRWa6YCOAV\nCNVQfn5++OWXX/Do0SOEh4djwoQJmDdvHsaMGYPs7Gxs2bJF7a9wW1tb6d+HDh3Cpk2b1I4rCAK6\ndu2q1m5paYmvv/4aX331lcq2kyZNgoWFBQBg4cKF0lNYCxYswIIFC6RtDQwMsGDBAqnzvSJSU1Px\n1VdfqZy7WN26daUnqxYvXoyJEyciPz8fS5cuxdKlS1W2bd++fYXPTa83XoHQa6+k2zoWFhYYP348\nBEGAKIpYvXo1HB0dsX//fowaNQpNmzaFkZERzMzM0Lx5cwwfPhwLFy6U9v/www/RqVMnNGrUCEZG\nRqhTpw6aN2+O6dOnY86cOWrnc3R0RGhoKFq1agVjY2PY2Nhgzpw5KmvVd+jQAT/++CP69+8PKysr\nGBoawtzcHD169MD27dsxYMAAtfdV0nt7ub1ly5b44IMP4OTkBDMzMxgaGsLS0hIeHh7Ytm0bGjZs\nCOD5WJWff/4ZQ4YMgbW1NWrXrg1zc3O4uLjA29sbn376acV/+PRa45roRFrk4uICQRDg7u6Obdu2\n6bocokrFKxAiLePfaPS6Yh8IkRYV30oq7ekoouqMt7CIiEgjvIVFREQaYYAQEZFGGCBERKQRBggR\nEWmEAUJERBr5/0Fk26xfqROrAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc68a709810>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results = cohort.plot_benefit({'Has Visceral Mets': VisceralMets}, plot_col = 'Has Visceral Mets')\n",
    "fishers_exact_hyper_label_printer(results, 'viseralmets')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mann-Whitney test: U=94.0, p-value=0.865039871052 (two-sided)\n",
      "{{{packyears_plot}}}\n",
      "{{{packyears_benefit:10.00 (range 0.00-100.00)}}}\n",
      "{{{packyears_no_benefit:12.50 (range 0.00-75.00)}}}\n",
      "{{{packyears_mw:n=29, Mann-Whitney p=0.87}}}\n"
     ]
    },
    {
     "data": {
      "image/png": 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wrOsSIiLiVAoVERGxjEJFREQso1ARERHLKFRERMQyChUREbGMQkVERCyjUBER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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc6b474d890>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results = cohort.plot_benefit('Pack Years')\n",
    "mann_whitney_hyper_label_printer(results, 'packyears')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# no condition 18\n",
      "# with condition 11\n",
      "{{{liver_pfs_logrank:n=29, log-rank p=0.024}}}\n",
      "# no condition 18\n",
      "# with condition 11\n",
      "{{{liver_os_plot}}}\n",
      "{{{liver_os_logrank:n=29, log-rank p=0.018}}}\n"
     ]
    },
    {
     "data": {
      "image/png": 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FGhERwdSpUzl27FiReT/99FNUKhV79+7FxsaGgwcPKv3SkP/Nql+/fjx48ICFCxeyYsUK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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc689c23ad0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(2, figsize=(5, 10))\n",
    "\n",
    "from utils.paper import logrank_formatter, hyper_label_printer\n",
    "results = cohort.plot_survival(on={'Liver Metastasis': LiverMets},\n",
    "                               with_condition_label='With Liver Metastasis',\n",
    "                               no_condition_label = 'Without Liver Metastasis',\n",
    "                               how='pfs', \n",
    "                               ax=ax[0])\n",
    "hyper_label_printer(logrank_formatter, \"%s_logrank\" % \"liver_pfs\", results=results)\n",
    "results = cohort.plot_survival(on={'Liver Metastasis': LiverMets},\n",
    "                               with_condition_label='With Liver Metastasis',\n",
    "                               no_condition_label = 'Without Liver Metastasis',\n",
    "                               how='os', \n",
    "                               ax=ax[1])\n",
    "survival_hyper_label_printer(results, \"liver_os\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# no condition 10\n",
      "# with condition 19\n",
      "Results\n",
      "   df: 1\n",
      "   alpha: 0.95\n",
      "   t 0: -1\n",
      "   test: logrank\n",
      "   null distribution: chi squared\n",
      "\n",
      "   __ p-value ___|__ test statistic __|____ test result ____|__ is significant __\n",
      "         0.01950 |              5.456 |      Reject Null    |        True       \n",
      "{{{visceral_os_plot}}}\n",
      "{{{visceral_os_logrank:n=29, log-rank p=0.020}}}\n"
     ]
    },
    {
     "data": {
      "image/png": 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u3buxe/duODo64vPPP4eDg4N0aYmISKeoLJlhw4ZBJpNBEARYWlrCyckJcrkc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\nImIbhYyIiNhGISMiIrb5C350Idocm0XyAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc68a438c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results = cohort.plot_survival(on={'Visceral Metastasis': VisceralMets},\n",
    "                               with_condition_label='With Visceral Metastasis',\n",
    "                               no_condition_label = 'Without Visceral Metastasis',\n",
    "                               how='os')\n",
    "results.print_summary()\n",
    "survival_hyper_label_printer(results, \"visceral_os\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Missing Five Factor Score = 0 or 1 for 3 patients: from 29 to 26\n",
      "# no condition 16\n",
      "# with condition 10\n",
      "Results\n",
      "   df: 1\n",
      "   alpha: 0.95\n",
      "   t 0: -1\n",
      "   test: logrank\n",
      "   null distribution: chi squared\n",
      "\n",
      "   __ p-value ___|__ test statistic __|____ test result ____|__ is significant __\n",
      "         0.31186 |              1.023 |  Cannot Reject Null |       False       \n",
      "{{{fivefactor_pfs_plot}}}\n",
      "{{{fivefactor_pfs_logrank:n=26, log-rank p=0.31}}}\n"
     ]
    },
    {
     "data": {
      "image/png": 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69evh5OSEDz74AE5OTlBRqfPclE1WXnLNRx7q2mpcw56ImiRRofLbb78hKSkJ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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc68898a290>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results = cohort.plot_survival(\n",
    "    on={'Five Factor Score = 0 or 1': FiveFactorScore01},\n",
    "    how='pfs',\n",
    "    with_condition_label='Five Factor Score = 0 or 1',\n",
    "    no_condition_label = 'Five Factor Score = 2, 3, 4'\n",
    ")\n",
    "results.print_summary()\n",
    "survival_hyper_label_printer(results, \"fivefactor_pfs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Missing Five Factor Score = 0 or 1 for 3 patients: from 29 to 26\n",
      "# no condition 16\n",
      "# with condition 10\n",
      "Results\n",
      "   df: 1\n",
      "   alpha: 0.95\n",
      "   t 0: -1\n",
      "   test: logrank\n",
      "   null distribution: chi squared\n",
      "\n",
      "   __ p-value ___|__ test statistic __|____ test result ____|__ is significant __\n",
      "         0.12592 |              2.342 |  Cannot Reject Null |       False       \n",
      "{{{fivefactor_os_plot}}}\n",
      "{{{fivefactor_os_logrank:n=26, log-rank p=0.13}}}\n"
     ]
    },
    {
     "data": {
      "image/png": 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FSubixYuQSCQIDAxEUFAQJBIJ9u7di9WrV+P27dtYvXq12DnrhKy7WdV+jK6+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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc688ea27d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results = cohort.plot_survival(on={'Five Factor Score = 0 or 1': FiveFactorScore01},\n",
    "                               how='os',\n",
    "                               with_condition_label='Five Factor Score = 0 or 1',\n",
    "                               no_condition_label = 'Five Factor Score = 2, 3 or 4'\n",
    "                              )\n",
    "results.print_summary()\n",
    "survival_hyper_label_printer(results, \"fivefactor_os\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
